A Transfer Learning Evaluation of Deep Neural Networks for Image Classification
Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achieving high performance while saving training time, mem...
Main Authors: | Nermeen Abou Baker, Nico Zengeler, Uwe Handmann |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-01-01
|
Series: | Machine Learning and Knowledge Extraction |
Subjects: | |
Online Access: | https://www.mdpi.com/2504-4990/4/1/2 |
Similar Items
-
Rock image classification using deep residual neural network with transfer learning
by: Weihao Chen, et al.
Published: (2023-01-01) -
Selected technical issues of deep neural networks for image classification purposes
by: M. Grochowski, et al.
Published: (2019-04-01) -
Hyperspectral Image Classification Based on Superpixel Pooling Convolutional Neural Network with Transfer Learning
by: Fuding Xie, et al.
Published: (2021-03-01) -
Deep Convolution Neural Network sharing for the multi-label images classification
by: Solemane Coulibaly, et al.
Published: (2022-12-01) -
Deep Learning Implementation using Convolutional Neural Network for Alzheimer’s Classification
by: Adhigana Priyatama, et al.
Published: (2023-03-01)